Generally in mines, mining work machines such as hydraulic shovels and dump trucks are used for excavation work and transportation work of earth and sand. For the mining work machines used at mines, an unmanned operation is required from the viewpoint of safety and cost reduction. In the dump truck, because the amount of earth and sand transported per unit time is directly related to the degree of progress of mining, an efficient operation is required. Therefore, in order to transport a large amount of earth and sand efficiently to the outside of the mining site, a mining system which uses an autonomous dump truck capable of performing a continuous operation has been required.
However, since a traveling road at a mine through which a dump truck travels is an off-road and there are many rough roads, when causing a dump truck to autonomously travel and perform an unmanned operation, there is a risk of a collision with an obstacle such as a mud wall or another vehicle. if an obstacle exists on the traveling road and an autonomous traveling unmanned dump truck comes into contact with the obstacle and stops, the operation of the mine is stopped for a long time. Therefore, in order to improve the reliability of the autonomous traveling dump truck, there is a need for an obstacle detection system having high reliability which is capable of detecting a preceding vehicle or the obstacles on the traveling road in the early stage, thereby performing the following travel to the preceding vehicle or the avoiding travel to the obstacle.
In related art, an obstacle detection apparatus such as a millimeter wave radar, a laser sensor, a camera, and a stereo camera is used as this kind of preceding vehicle and obstacle detection system. The millimeter wave radar has high environmental resistance to operate even when dust, rain, or the like occurs, and has high measurement range performance. Meanwhile, since the stereo camera or the laser sensor can measure a three-dimensional shape, it is possible to accurately detect an obstacle on the road. There is also a method of improving the obstacle detection performance by combining these sensors.
In order to use a plurality of sensors of different types, it is necessary to accurately grasp the relative position of each sensor. Especially, when attaching the sensors to a mining dump truck, since the car body is large, it is necessary to consider positional deviation due to aging in addition to the calibration at the time of attachment. For example, PTL 1 discloses an obstacle recognition device that corrects the axial deviation of an in-vehicle camera and an in-vehicle radar caused due to aging, based on position information of an obstacle detected by each sensor.